Fan, Wenqi

A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

Fan, W., Ding, Y., Ning, L., Wang, S., Li, H., Yin, D., Chua, T.-S., & Li, Q. (2024) · Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Topic ModelingInformation Retrieval and Search Behavior

Cited by 827

Recommender Systems in the Era of Large Language Models (LLMs)

Zhao, Z., Fan, W., Li, J., Liu, Y., Mei, X., Wang, Y., Wen, Z., Wang, F., Zhao, X., Tang, J., et al. (2024) · IEEE Transactions on Knowledge and Data Engineering

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 481

Trustworthy AI: A Computational Perspective

Liu, H., Wang, Y., Fan, W., Liu, X., Li, Y., Jain, S., Liu, Y., Jain, A. K., & Tang, J. (2021) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 261

Trustworthy ai: A computational perspective

Liu, H., Wang, Y., Fan, W., Liu, X., Li, Y., Jain, S., Liu, Y., Jain, A., & Tang, J. (2023) · ACM Transactions on Intelligent Systems and Technology

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 261

Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs

Chen, Z., Mao, H., Li, H., Jin, W., Wen, H., Wei, X., Wang, S., Yin, D., Fan, W., Liu, H., et al. (2024) · ACM SIGKDD Explorations Newsletter

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 209

Knowledge-enhanced Black-box Attacks for Recommendations

Chen, J., Fan, W., Zhu, G., Zhao, X., Yuan, C., Li, Q., & Huang, Y. (2022) · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Recommender Systems and TechniquesAdversarial Robustness in Machine Learning

Cited by 49

Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles

Fan, W., Zhao, X., Li, Q., Derr, T., Ma, Y., Liu, H., Wang, J., & Tang, J. (2023) · IEEE Transactions on Knowledge and Data Engineering

Recommender Systems and TechniquesAdversarial Robustness in Machine Learning

Cited by 41

A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models

Ning, L., Liang, Z., Jiang, Z., Qu, H., Ding, Y., Fan, W., Wei, X.-Y., Lin, S., Liu, H., Yu, P. S., et al. (2025) · arXiv

Web Data Mining and AnalysisInformation Retrieval and Search Behavior

Cited by 30

CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent

Ning, L.-B., Wang, S., Fan, W., Li, Q., Xu, X., Chen, H., & Huang, F. (2024) · Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Adversarial Robustness in Machine LearningRecommender Systems and Techniques

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